CN114882666B - Smart home fire early warning method, smart home fire early warning system, terminal equipment and storage medium - Google Patents
Smart home fire early warning method, smart home fire early warning system, terminal equipment and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of intelligent home control, which comprises an intelligent home fire early warning method, an intelligent home fire early warning system, terminal equipment and a storage medium, wherein the intelligent home fire early warning method comprises the following steps: acquiring indoor real-time temperature; analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information; detecting the indoor environment in real time according to the early warning information, and obtaining a detection result; and generating a feedback instruction according to the detection result, and executing corresponding target operation according to the feedback instruction. The intelligent household fire early warning method, the system, the terminal equipment and the storage medium provided by the application have the effect of reasonably early warning according to the actual condition of the fire.
Description
Technical Field
The application relates to the technical field of intelligent home control, in particular to an intelligent home fire early warning method, an intelligent home fire early warning system, terminal equipment and a storage medium.
Background
The intelligent home uses the home as a platform, integrates facilities related to home life by utilizing a comprehensive wiring technology, a network communication technology, a security technology, an automatic control technology and an audio and video technology, and constructs an efficient management system for home facilities and family schedule matters.
In modern family life, indoor household articles are various, and most indoor household articles belong to inflammable articles, fire is easy to catch fire, and for the problem that indoor household articles catch fire, a traditional fire early warning system mainly carries out fire early warning through a smoke monitoring method.
When a fire disaster occurs, the traditional fire disaster early warning system cannot effectively judge in real time according to the situation of fire disaster development, and therefore reasonable early warning is not facilitated according to the actual situation of the fire disaster.
Disclosure of Invention
In order to make reasonable early warning according to the actual condition of fire, the application provides an intelligent household fire early warning method, system, terminal equipment and storage medium.
In a first aspect, the intelligent household fire disaster early warning method provided by the application adopts the following technical scheme:
A fire early warning method for smart home comprises the following steps:
Acquiring indoor real-time temperature;
Analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information;
Detecting the indoor environment in real time according to the early warning information, and obtaining a detection result;
And generating a feedback instruction according to the detection result, and executing corresponding target operation according to the feedback instruction.
By adopting the technical scheme, the indoor real-time temperature is acquired, and then the real-time temperature and the preset early-warning temperature interval are analyzed to form and broadcast corresponding early-warning information.
Optionally, the early warning information includes first early warning information, and the analyzing the real-time temperature and the preset early warning temperature interval to form and broadcast the early warning information includes the following steps:
judging whether the real-time temperature is in the early warning temperature interval or not;
If the first early warning information is in the early warning temperature interval, acquiring the first early warning information;
acquiring a first decibel value corresponding to the first early warning information according to a preset broadcasting rule;
And broadcasting the first early warning information according to the first decibel value.
By adopting the technical scheme, if the indoor real-time temperature is in the preset early warning temperature interval, the first early warning information which is matched with the first decibel value of the first early warning information, so that reasonable early warning can be carried out according to the actual condition of fire development.
Optionally, the early warning information includes second early warning information, and further includes the following steps:
if the real-time temperature is not in the early warning temperature interval, judging whether the real-time temperature is higher than the early warning temperature interval or not;
if the temperature is higher than the early warning temperature interval, obtaining the second early warning information;
acquiring a second score Bei Zhi corresponding to the second early warning information according to the preset broadcasting rule;
and broadcasting the first early warning information according to the second decibel value.
By adopting the technical scheme, the early warning temperature interval is used as a standard, whether the real-time temperature is higher than the early warning temperature interval is judged, and whether the fire is more intense on the existing basis can be further obtained, so that the real-time judgment on the fire can be effectively carried out.
Optionally, the indoor environment includes home power-on information, and the detecting the indoor environment in real time according to the early warning information, and obtaining a detection result includes the following steps:
Acquiring the household power-on information according to the early warning information;
detecting the household electrifying information in real time to obtain electrifying data parameters;
Judging whether the power-on data parameters are abnormal or not;
if the current is abnormal, judging that the detection result is an electrifying abnormal result.
By adopting the technical scheme, when a fire disaster occurs, indoor environment information such as household power-on information is detected, and then a normal or abnormal result is obtained, so that potential dangerous sources can be early warned.
Optionally, the generating a feedback instruction according to the detection result, and executing the corresponding target operation according to the feedback instruction includes the following steps:
generating power-off prompt information according to the power-on abnormal result;
the feedback instruction generated according to the power-off prompt information is a light supplementing instruction;
And executing light supplementing operation according to the light supplementing instruction.
Through adopting above-mentioned technical scheme, can accompany a large amount of smog when the conflagration takes place, the indoor visibility has been reduced greatly to the existence of smog, through carrying out the light filling to it to promoted indoor visibility, be favorable to the rescue work of later stage.
Optionally, the indoor environment includes smoke concentration information, and the performing the light filling operation according to the light filling instruction includes the following steps:
acquiring the smoke concentration information according to a light supplementing instruction;
Detecting the smoke concentration information in real time to obtain a concentration data parameter;
generating a light compensation brightness parameter according to the concentration data parameter;
And executing light supplementing operation according to the light supplementing brightness parameters.
By adopting the technical scheme, the light compensation brightness is adaptively adjusted according to the change of the smoke concentration data parameters and the light compensation brightness parameters, so that the indoor visibility is effectively improved.
Optionally, after the light supplementing operation is performed according to the light supplementing instruction, the method further includes the following steps:
Recording the duration of the light supplement;
Judging whether the duration of the light supplementing exceeds a preset duration;
And if the preset time period is exceeded, contacting the target person through a preset contact mode.
By adopting the technical scheme, if the duration of the light supplementing exceeds the preset duration, the fire can not be controlled, and the fire can be rescued by the target personnel by timely contacting the target personnel.
In a second aspect, the application provides an intelligent household fire early warning system, which adopts the following technical scheme:
an intelligent home fire early warning system, comprising:
The acquisition module is used for acquiring indoor real-time temperature;
the analysis module is used for analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information;
The detection module is used for detecting the indoor environment in real time according to the early warning information and obtaining a detection result;
And the processing module is used for generating a feedback instruction according to the detection result and executing corresponding target operation according to the feedback instruction.
Through adopting above-mentioned technical scheme, obtain indoor real-time temperature through obtaining the module, then carry out analysis formation and report corresponding early warning information through analysis module with real-time temperature and the early warning temperature interval of predetermineeing, compare with prior art, when the conflagration breaks out, according to indoor real-time temperature variation, and then obtain the early warning information that suits, carry out real-time supervision to indoor environment through detection module when obtaining early warning information, gather indoor environment data information and further obtain the testing result, generate corresponding feedback instruction and corresponding target operation through processing module according to the testing result, thereby can make reasonable early warning according to the actual conditions of conflagration.
In a third aspect, the present application provides a terminal device, which adopts the following technical scheme:
The terminal equipment comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the intelligent household fire early warning method is adopted when the processor loads and executes the computer program.
By adopting the technical scheme, the intelligent household fire disaster early warning method generates the computer program, stores the computer program in the memory and loads and executes the computer program by the processor, so that the terminal equipment is manufactured according to the memory and the processor, and is convenient to use.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
A computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and when the computer program is loaded and executed by a processor, the intelligent household fire early warning method is adopted.
By adopting the technical scheme, the intelligent household fire disaster early warning method generates the computer program, stores the computer program in the computer readable storage medium to be loaded and executed by the processor, and facilitates the reading and storage of the computer program through the computer readable storage medium.
In summary, the present application includes at least one of the following beneficial technical effects: the method comprises the steps of acquiring indoor real-time temperature, analyzing the real-time temperature and a preset early warning temperature interval, and further obtaining corresponding early warning information according to an analysis result.
Drawings
Fig. 1 is a schematic overall flow chart of an intelligent household fire early warning method of the application.
Fig. 2 is a schematic flow chart of step S201 to step S204 in the smart home fire disaster early warning method of the present application.
Fig. 3 is a schematic flow chart of steps S301 to S304 in the smart home fire disaster early warning method of the present application.
Fig. 4 is a schematic flow chart of step S401 to step S404 in the smart home fire disaster early warning method of the present application.
Fig. 5 is a schematic flow chart of steps S501 to S503 in the smart home fire disaster early warning method of the present application.
Fig. 6 is a schematic flow chart of steps S601 to S604 in the smart home fire disaster early warning method of the present application.
Fig. 7 is a schematic flow chart of steps S701-S703 in the smart home fire disaster early warning method of the present application.
Fig. 8 is a schematic diagram of an overall module of an intelligent home fire early warning system according to the present application.
Reference numerals illustrate:
1. An acquisition module; 2. an analysis module; 3. a detection module; 4. and a processing module.
Detailed Description
The application is described in further detail below with reference to fig. 1-8.
The embodiment of the application discloses an intelligent household fire disaster early warning method, which comprises the following steps with reference to fig. 1:
s101, acquiring indoor real-time temperature;
s102, analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information;
S103, detecting the indoor environment in real time according to the early warning information, and obtaining a detection result;
S104, generating a feedback instruction according to the detection result, and executing corresponding target operation according to the feedback instruction.
In the practical application, the step S101 may collect real-time temperature data of the target monitoring area through a temperature sensor, and the metal will generate a corresponding extension after the environmental temperature changes, so the temperature sensor may perform signal conversion on the reaction in different manners, and may be divided into two types, i.e. contact type and non-contact type, according to the measurement manner, and two types, i.e. thermal resistor and thermocouple, according to the sensor material and electronic element characteristics. The resistance value of the metal-based temperature sensor changes along with the change of the temperature, and the resistance value is different for each degree of temperature change of different metals, and can be directly used as an output signal.
In the actual application of step S102, the ignition point of the plain paper is generally between 130 and 255.5 degrees, and in order to reduce false alarm, the alarm temperature is set at 120 degrees by default, and the early warning temperature interval is preset to 120 to 130 degrees according to the alarm temperature. And analyzing the acquired indoor real-time temperature data and a preset early warning temperature interval to form and broadcasting corresponding early warning information through an alarm system.
In the practical application, the alarm system broadcasts corresponding early warning information when the indoor real-time temperature exceeds the alarm temperature, and detects the indoor environment while broadcasting the early warning information, wherein the indoor environment can be household power-on information, smoke concentration information, indoor natural gas content information and the like, so as to obtain corresponding data parameters, and whether the data parameters of the indoor environment accord with corresponding normal parameter values is detected and judged, so that a corresponding detection result is obtained. And according to the detection result of the indoor environment, generating a corresponding feedback instruction, and executing corresponding target operation by the system according to the feedback instruction.
In one implementation manner of this embodiment, the early warning information includes first early warning information, as shown in fig. 2, and step S102 includes the following steps:
S201, judging whether the real-time temperature is in an early warning temperature interval or not;
s202, if the temperature range is within the early warning temperature range, obtaining first early warning information;
S203, acquiring a first decibel value corresponding to the first early warning information according to a preset broadcasting rule;
S204, broadcasting first early warning information according to the first decibel value.
In the actual application, the early warning information in step S201 to step S202 refers to early warning prompt information when a serious fire occurs or is likely to occur, and judges whether the acquired real-time temperature is within a preset early warning temperature interval, if so, corresponding first early warning information is obtained.
It should be noted that, the indoor space can be recorded by the AI camera, when the activity of a person is detected, the system is automatically set to a low early warning state, and when the space has no activity of a person, the system is automatically set to a safety mode. The indoor real-time temperature is acquired through the temperature sensor, the indoor real-time temperature is 125 ℃, the system analyzes and compares the real-time temperature with a preset early-warning temperature interval to obtain that the indoor real-time temperature is in the preset early-warning temperature interval, first early-warning information is automatically generated, the first early-warning information can be set as a voice prompt of 'having found a fire source, requesting to make fire extinguishing treatment in time', or can be set as a fire alarm bell,
In the practical application, step S203-step S204 obtain a first db value corresponding to the first warning information according to a preset broadcasting rule, where the first db value is adapted to a specific temperature value of the real-time temperature, the first db value is set to be 50 db, and the AI camera sends the first warning information of 50 db through the speaker.
In one implementation of this embodiment, the early warning information includes second early warning information, as shown in fig. 3, and step S102 further includes the following steps:
S301, if the real-time temperature is not in the early warning temperature interval, judging whether the real-time temperature is higher than the early warning temperature interval;
S302, if the temperature is higher than the early warning temperature interval, obtaining second early warning information;
S303, acquiring a second score Bei Zhi corresponding to the second early warning information according to a preset broadcasting rule;
S304, broadcasting the first early warning information according to the second score Bei Zhi.
In the actual application, step S301-step S302, if the obtained indoor real-time temperature is not in the preset early-warning temperature interval, it is determined whether the real-time temperature is higher than the early-warning temperature interval, and if so, second early-warning information corresponding to the real-time temperature is obtained.
It should be noted that, the real-time temperature in the room is 140 degrees, the real-time temperature is higher than the pre-warning temperature interval by judging, the second pre-warning information matched with the real-time temperature is obtained, the real-time temperature at this time is higher than the conventional pre-warning temperature in consideration of weak fire-fighting consciousness of the old and the children, the risk degree is higher, the second pre-warning information can be set as a fire extinguishing mode in the initial stage and some caution items for escaping in order to enhance the self-rescue capability,
In the actual application, step S303-step S304 obtain a second decibel value corresponding to the second early warning information according to the second early warning information, and in order to warn the dangerous degree of fire, the second decibel value is set to 75 db correspondingly, and the AI camera sends the second early warning information of 75 db through the speaker.
In one implementation of the present embodiment, the indoor environment includes home power-on information, and as shown in fig. 4, step S103 includes the steps of:
s401, acquiring household power-on information according to the early warning information;
S402, detecting household power-on information in real time to obtain power-on data parameters;
s403, judging whether the power-on data parameters are abnormal;
s404, if the power-on abnormality occurs, the detection result is judged to be the power-on abnormality result.
In actual application, when the system sends out early warning information, the step S401-step S402 analyzes the indoor environment, the indoor environment can be household power-on information, when a fire disaster occurs, a household power-on line is affected by the fire disaster, the dangerous degree of the fire disaster can be promoted, and corresponding power-on data parameters are obtained by detecting the household power-on information in real time.
It should be noted that, in daily life, fire occurs indoors, the indoor household power transmission line may cause danger of electric leakage after long-time burning, the system sends out early warning information and simultaneously continuously acquires household power-on information, and corresponding power-on data parameters are obtained by detecting the household power-on information.
In the actual application, step S403 to step S404 can obtain whether the energization data parameter is abnormal or not by analyzing the energization data parameter, and the energization line may be short-circuited or open-circuited due to high temperature, and the short-circuited or open-circuited may cause the energization data parameter to be abnormal, thereby causing an indoor power failure.
In one implementation of the present embodiment, as shown in fig. 5, step S104 includes the following steps:
S501, generating power-off prompt information according to a power-on abnormal result;
s502, a feedback instruction generated according to the power-off prompt information is a light supplementing instruction;
s503, executing light supplementing operation according to the light supplementing instruction.
In the actual application, step S501-step S503 generate power-off prompt information according to the power-on abnormal result, and the system generates and sends a corresponding light-compensating instruction to the light-compensating device according to the power-off prompt information, and the light-compensating device supplements light to the indoor target area according to the light-compensating instruction.
It should be noted that, the light supplementing device may be set as an AI camera, the system sends the power failure prompt information to the AI camera, and the AI camera is internally provided with a high-capacity lithium battery as a power supply of the device after the fire disaster and the power failure occur. When a fire disaster occurs, the AI camera receives and recognizes the power-off prompt information and can emit yellow warm light to supplement light, so that the penetrating power of light is increased.
In one implementation of this embodiment, the indoor environment includes smoke concentration information, and as shown in fig. 6, step S503 includes the steps of:
S601, acquiring smoke concentration information according to a light supplementing instruction;
S602, detecting smoke concentration information in real time to obtain concentration data parameters;
s603, generating a light compensation brightness parameter according to the concentration data parameter;
S604, executing light supplementing operation according to the light supplementing brightness parameters.
In the practical application, the step S601-step S602 generates a large amount of smoke while the fire disaster occurs, the concentration of the smoke can influence the indoor visibility, the system acquires indoor smoke concentration information according to a light supplementing instruction, the fire disaster smoke is a mixture composed of gas, liquid and solid particle groups, the fire disaster smoke has physical characteristics of volume, mass, temperature, charge and the like, the fire disaster smoke can be detected through an ionic smoke detector, and the ionic smoke detector is a micro-current change device for sensing smoke ions through voltage change caused by an ionization chamber corresponding to a smoke-sensitive resistor. When smoke ions enter the ionization chamber, the ionization state of air in the ionization chamber is changed, so that macroscopic change is realized that the equivalent resistance of the ionization chamber is increased to cause the voltage at two ends of the ionization chamber to be increased, the smoke condition in the air is determined, and the concentration data parameters of the smoke are acquired according to the smoke condition.
In the actual application, the step S603-step S604 matches the obtained concentration data parameter of the smoke to the corresponding light-compensating parameter, the light-compensating parameter changes along with the change of the concentration data parameter, the AI camera generates the corresponding light-compensating parameter according to the change of the concentration data parameter, and the AI camera adaptively adjusts the light-compensating according to the light-compensating parameter.
In one implementation of this embodiment, the indoor environment includes smoke concentration information, as shown in fig. 7, and the following steps are further included after step S503:
S701, recording the duration of light filling;
s702, judging whether the duration of the light supplementing exceeds the preset duration;
s703, if the preset time period is exceeded, contacting the target person through a preset contact mode.
In the actual application, the AI camera starts recording the duration of light filling while performing light filling, and if the duration of light filling exceeds the preset duration and no person is processing, the system automatically contacts the target person through the preset contact mode.
It should be noted that, the preset time length of light filling is 1 minute, the AI camera records the time length of light filling while performing light filling, if the recorded time length is more than 1 minute, the AI camera inputs the stored emergency contact number in advance and calls the emergency contact number if the related person does not catch the fire disaster through image acquisition, the early warning information broadcasting is performed if the emergency contact number is dialed, and if the emergency contact number cannot be dialed, the indoor fire disaster picture captured by the AI camera is sent to the mailbox of the emergency contact.
The implementation principle of the intelligent household fire disaster early warning method provided by the embodiment of the application is as follows: acquiring real-time indoor temperature, and comparing the real-time temperature with a preset early warning temperature interval to acquire and broadcast corresponding early warning information; in order to further detect potential dangerous factors when a fire disaster occurs, real-time detection is carried out on the indoor environment while early warning information is obtained, corresponding data parameters are obtained, analysis is carried out on the data parameters, corresponding detection results are obtained, corresponding feedback instructions are generated according to the detection results, and the system executes corresponding target operation according to the feedback instructions. The intelligent household fire disaster early warning method provided by the application can reasonably early warn according to the actual condition of the fire disaster.
The embodiment of the application discloses an intelligent household fire early warning system, which is shown in fig. 8, and comprises an acquisition module 1, an analysis module 2, a detection module 3 and a processing module 4, wherein the acquisition module 1 is used for acquiring indoor real-time temperature; the analysis module 2 is used for analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information; the detection module 3 is used for detecting the indoor environment in real time according to the early warning information and obtaining a detection result; the processing module 4 is configured to generate a feedback instruction according to the detection result, and execute a corresponding target operation according to the feedback instruction.
In actual application, acquiring temperature real-time data of a target monitoring area through an acquisition module 1, transmitting the acquired temperature real-time data to an analysis module 2 by the acquisition module 1 for analysis, obtaining a corresponding analysis result through analysis, and sending early warning information according to the analysis result by a system; the detection module 3 detects the indoor environment in real time while recognizing the early warning information to obtain a corresponding detection result, and sends the detection result to the processing module 4, and the processing module 4 generates a corresponding feedback instruction according to the detection result and executes corresponding target operation according to the feedback instruction.
It should be noted that, the acquiring module 1 may be configured as a temperature sensor, and the temperature sensor is used to acquire real-time temperature data of the target monitoring area, and the metal will generate a corresponding extension after the environmental temperature changes, so that the temperature sensor may perform signal conversion on the reaction in different manners, and may be classified into two types, namely, contact type and non-contact type according to the measurement manner, and may be classified into two types, namely, thermal resistor and thermocouple according to the sensor material and electronic element characteristics. The resistance value of the metal-based temperature sensor changes along with the change of the temperature, and the resistance value is different for each degree of temperature change of different metals, and can be directly used as an output signal.
In practical application, in order to reduce false alarm, the alarm temperature is set at 120 degrees by default, and the early-warning temperature interval is preset to 120-130 degrees according to the alarm temperature. And the analysis module 2 analyzes the acquired indoor real-time temperature data and a preset early warning temperature interval, and corresponding early warning information is formed and broadcasted through an alarm system.
It should be noted that the early warning information refers to early warning prompt information when a serious fire occurs or may occur, and the serious fire is caused or may occur. Judging whether the acquired real-time temperature is in a preset early warning temperature interval or not through an analysis module 2, if so, obtaining corresponding first early warning information and a first decibel value matched with the first early warning information, and broadcasting the first early warning information according to the first decibel value by a system; if the temperature is higher than the early warning temperature interval, automatically generating second early warning information and a second score value matched with the second early warning information, and broadcasting the second early warning information by the system according to the second score Bei Zhi.
The indoor real-time temperature is 140 degrees, the analysis module 2 judges that the real-time temperature is higher than the early warning temperature interval, then the second early warning information matched with the real-time temperature and the corresponding second decibel value are automatically generated, the fact that fire-fighting consciousness of the old and children is weak is considered, in order to enhance self-rescue capability, the second early warning information can be set to be voice information of an initial fire extinguishing mode and escape notice, the second decibel value is set to be 75 decibels, and the AI camera sends the second early warning information of 75 decibels through the loudspeaker.
In practical application, when the system sends out early warning information, the detection module 3 detects and analyzes the indoor environment, the indoor environment can be family power-on information, natural gas content information, inflammable and explosive information and other environment information, the environment information can promote the severity of fire when fire occurs, and the detection module 3 detects relevant data parameters, analyzes and identifies the relevant data parameters and obtains corresponding judgment information.
It should be noted that, the detection module 3 may be set as a data collector or a sensor corresponding to an indoor environment, where a fire disaster occurs indoors, and when the system sends out early warning information, the data collector continuously acquires household power-on information, further acquires data parameters of the ammeter, then judges whether an abnormality exists, if the abnormality exists, outputs an abnormal detection result, and the system automatically generates power-off prompt information according to the abnormal detection result.
In practical application, the system sends the power-off prompt information to the AI camera, and the AI camera is internally provided with a large-capacity lithium battery as a power supply of equipment after power failure in a fire disaster. When a fire disaster occurs, the AI camera receives and recognizes the power-off prompt information, a corresponding light supplementing instruction is generated through the processing module 4, the AI camera emits yellow warm light to supplement light according to the light supplementing instruction, the penetrating power of light is increased, the indoor smoke concentration can be collected through a smoke sensor arranged on the AI camera, further corresponding concentration data parameters are obtained, the specific condition of the indoor smoke concentration is obtained through analyzing the concentration data parameters, the processing module 4 generates the corresponding light supplementing instruction according to the change detection result of the data parameters along with the change of the concentration data parameters, and the AI camera adaptively carries out light supplementing adjustment according to the light supplementing instruction.
The AI camera starts to record the light supplementing time length and preset time length while supplementing light, if the light supplementing time length exceeds the preset time length and no personnel is processed, the processing module 4 generates a corresponding emergency contact instruction, and the system contacts the target personnel according to the emergency contact instruction through a preset contact mode. The preset time length of light filling is 1 minute, the AI camera records the time length while filling light, if the recorded time length is more than 1 minute, the AI camera does not capture related personnel to process fire through portrait collection, the query device inputs a stored emergency contact number in advance and calls the emergency contact number, if the emergency contact number is dialed, early warning information broadcasting is carried out, and if the emergency contact number cannot be dialed, an indoor fire scene captured by the AI camera is sent to a mailbox of the emergency contact.
The implementation principle of the intelligent household fire early warning system provided by the embodiment of the application is as follows: acquiring real-time indoor temperature through an acquisition module 1, and comparing the real-time temperature with a preset early warning temperature interval through an analysis module 2 to acquire and broadcast corresponding early warning information; in order to further detect potential risk factors when a fire disaster occurs, the indoor environment is detected in real time through the detection module 3 while early warning information is obtained, corresponding data parameters are obtained, the data parameters are analyzed, corresponding detection results are obtained, corresponding feedback instructions are generated through the processing module 4 according to the detection results, and the system executes corresponding target operations according to the feedback instructions. The intelligent household fire disaster early warning method provided by the application can reasonably early warn according to the actual condition of the fire disaster.
The embodiment of the application also discloses a terminal device which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the intelligent household fire early warning method in the embodiment is adopted when the processor executes the computer program.
The terminal device may be a computer device such as a desktop computer, a notebook computer, or a cloud server, and the terminal device includes, but is not limited to, a processor and a memory, for example, the terminal device may further include an input/output device, a network access device, a bus, and the like.
The processor may be a Central Processing Unit (CPU), or of course, according to actual use, other general purpose processors, digital Signal Processors (DSP), application Specific Integrated Circuits (ASIC), ready-made programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., and the general purpose processor may be a microprocessor or any conventional processor, etc., which is not limited in this respect.
The memory may be an internal storage unit of the terminal device, for example, a hard disk or a memory of the terminal device, or an external storage device of the terminal device, for example, a plug-in hard disk, a Smart Memory Card (SMC), a secure digital card (SD), or a flash memory card (FC) provided on the terminal device, or the like, and may be a combination of the internal storage unit of the terminal device and the external storage device, where the memory is used to store a computer program and other programs and data required by the terminal device, and the memory may be used to temporarily store data that has been output or is to be output, which is not limited by the present application.
The intelligent household fire early warning method in the embodiment is stored in the memory of the terminal device through the terminal device, and is loaded and executed on the processor of the terminal device, so that the intelligent household fire early warning method is convenient to use.
The embodiment of the application also discloses a computer readable storage medium, and the computer readable storage medium stores a computer program, wherein the intelligent household fire early warning method in the embodiment is adopted when the computer program is executed by a processor.
The computer program may be stored in a computer readable medium, where the computer program includes computer program code, where the computer program code may be in a source code form, an object code form, an executable file form, or some middleware form, etc., and the computer readable medium includes any entity or device capable of carrying the computer program code, a recording medium, a usb disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a Random Access Memory (RAM), an electrical carrier signal, a telecommunication signal, a software distribution medium, etc., where the computer readable medium includes, but is not limited to, the above components.
The intelligent household fire early warning method in the embodiment is stored in the computer readable storage medium through the computer readable storage medium, and is loaded and executed on a processor, so that the storage and the application of the method are convenient.
The above embodiments are not intended to limit the scope of the present application, so: all equivalent changes in structure, shape and principle of the application should be covered in the scope of protection of the application.
Claims (3)
1. The intelligent household fire disaster early warning method is characterized by adopting an intelligent household fire disaster early warning system, and comprises the following steps:
Acquiring indoor real-time temperature;
Analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information, setting the alarm temperature to 120 ℃, and presetting the early warning temperature interval to 120-130 ℃ according to the alarm temperature;
Detecting the indoor environment in real time according to the early warning information, obtaining a detection result, broadcasting corresponding early warning information by an alarm system when the indoor real-time temperature exceeds the alarm temperature, detecting the indoor environment while broadcasting the early warning information, acquiring corresponding data parameters by the indoor environment including household power-on information, smoke concentration information and indoor natural gas content information, and obtaining a corresponding detection result by detecting and judging whether the data parameters of the indoor environment accord with corresponding normal parameter values;
generating a feedback instruction according to the detection result, and executing corresponding target operation according to the feedback instruction;
the indoor environment comprises household power-on information, the indoor environment is detected in real time according to the early warning information, and a detection result is obtained, and the method comprises the following steps:
Acquiring the household power-on information according to the early warning information;
detecting the household electrifying information in real time to obtain electrifying data parameters;
Judging whether the power-on data parameters are abnormal or not, and analyzing the power-on data parameters to obtain whether the power-on data parameters are abnormal or not;
If the current is abnormal, judging that the detection result is an electrifying abnormal result;
the method for generating the feedback instruction according to the detection result and executing the corresponding target operation according to the feedback instruction comprises the following steps:
generating power-off prompt information according to the power-on abnormal result;
the feedback instruction generated according to the power-off prompt information is a light supplementing instruction;
Executing light supplementing operation according to the light supplementing instruction;
The system generates and sends a corresponding light supplementing instruction to the light supplementing equipment according to the power outage prompt information, the light supplementing equipment supplements light to an indoor target area according to the light supplementing instruction, the light supplementing equipment is set as an AI camera, the system sends the power outage prompt information to the AI camera, a large-capacity lithium battery is arranged in the AI camera and is used as a power supply of the equipment after the power outage of a fire disaster occurs, and when the fire disaster occurs, the AI camera receives and recognizes the power outage prompt information and sends yellow warm light to supplement light, so that the penetrating power of light is increased;
The indoor environment comprises smoke concentration information, and the light supplementing operation executed according to the light supplementing instruction comprises the following steps:
acquiring the smoke concentration information according to a light supplementing instruction;
Detecting the smoke concentration information in real time to obtain a concentration data parameter;
generating a light compensation brightness parameter according to the concentration data parameter;
performing light supplementing operation according to the light supplementing brightness parameters;
The system acquires indoor smoke concentration information according to a light supplementing instruction, the ionic smoke detector is used for detecting fire smoke, the ionic smoke detector is a micro-current change device for sensing smoke ions through voltage change caused by an ionization chamber of a smoke-sensitive resistor, when the smoke ions enter the ionization chamber, the ionization state of air in the ionization chamber is changed, macroscopic change is that the equivalent resistance of the ionization chamber is increased to cause voltage increase at two ends of the ionization chamber, so that smoke conditions in the air are determined, and concentration data parameters of the smoke are acquired according to the smoke conditions; according to the obtained concentration data parameters of the smoke, matching the obtained concentration data parameters to corresponding light-supplementing brightness parameters, wherein the light-supplementing brightness parameters change along with the change of the concentration data parameters, and the AI camera generates corresponding light-supplementing brightness parameters according to the change of the concentration data parameters, so that the AI camera adaptively adjusts the light-supplementing brightness according to the light-supplementing brightness parameters;
The method further comprises the following steps after the light supplementing operation is executed according to the light supplementing instruction:
Recording the duration of the light supplement;
Judging whether the duration of the light supplementing exceeds a preset duration;
if the preset time length is exceeded, contacting the target person through a preset contact mode;
The method comprises the steps that when the AI camera is used for supplementing light, the continuous time length of the light supplementing is recorded, if the continuous time length of the light supplementing exceeds a preset time length and no personnel is used for processing, the system automatically contacts a target person through a preset contact mode, the preset time length of the light supplementing is 1 minute, if the recorded time length exceeds 1 minute, the AI camera is used for acquiring a person and not capturing related personnel to process a fire disaster, a query device inputs a stored emergency contact number in advance and calls the emergency contact number, if the number of the emergency contact is dialed, early warning information broadcasting is carried out, and if the number of the emergency contact cannot be dialed, an indoor fire disaster picture captured by the AI camera is sent to a mailbox of the emergency contact;
The early warning information comprises first early warning information, and the early warning information is formed and broadcasted by analyzing the real-time temperature and a preset early warning temperature interval, and comprises the following steps:
judging whether the real-time temperature is in the early warning temperature interval or not;
If the first early warning information is in the early warning temperature interval, acquiring the first early warning information;
acquiring a first decibel value corresponding to the first early warning information according to a preset broadcasting rule;
Broadcasting the first early warning information according to the first decibel value;
Recording an indoor space through an AI (advanced technology) camera, automatically setting a system to a low early warning state when people are detected to move, automatically setting the system to a safe mode when no people move in the space, acquiring indoor real-time temperature through a temperature sensor, acquiring the indoor real-time temperature to 125 ℃, analyzing and comparing the real-time temperature with a preset early warning temperature interval by the system to obtain that the indoor real-time temperature is lower than the preset early warning temperature interval, automatically generating first early warning information, setting the first early warning information to be a voice prompt of 'found ignition source, requesting to perform fire extinguishing treatment in time', setting a first decibel value to be 50 decibels according to a specific temperature value of the real-time temperature, and sending 50 decibels of first early warning information through a loudspeaker by the AI camera;
The early warning information comprises second early warning information and further comprises the following steps:
if the real-time temperature is not in the early warning temperature interval, judging whether the real-time temperature is higher than the early warning temperature interval or not;
if the temperature is higher than the early warning temperature interval, obtaining the second early warning information;
acquiring a second score Bei Zhi corresponding to the second early warning information according to the preset broadcasting rule;
broadcasting the first early warning information according to the second decibel value;
The method comprises the steps of obtaining the indoor real-time temperature to be 140 ℃, obtaining second early warning information matched with the real-time temperature through judging that the real-time temperature is higher than an early warning temperature interval, setting the second early warning information to be a series of notes of an initial fire extinguishing mode and escape, setting a second decibel value to be 75 decibels, and sending the second early warning information of 75 decibels through a loudspeaker by an AI (analog to digital) camera;
the intelligent household fire disaster early warning system comprises:
the system comprises an acquisition module (1), wherein the acquisition module (1) is used for acquiring indoor real-time temperature;
The analysis module (2) is used for analyzing the real-time temperature and a preset early warning temperature interval to form and broadcast early warning information;
The detection module (3) is used for detecting the indoor environment in real time according to the early warning information and obtaining a detection result;
And the processing module (4) is used for generating a feedback instruction according to the detection result and executing corresponding target operation according to the feedback instruction.
2. A terminal device comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, characterized in that the method of claim 1 is used when the processor loads and executes the computer program.
3. A computer readable storage medium having a computer program stored therein, characterized in that the method of claim 1 is employed when the computer program is loaded and executed by a processor.
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